[P2–011]: INCREASED PRO‐INFLAMMATORY SIGNALING AND EVIDENCE OF ALZHEIMER's DISEASE PATHOLOGY IN HEALTHY OLDER ADULTS AT RISK FOR AD
Bibliographic record
Abstract
Growing evidence suggests altered immune responses in the development of Alzheimer's Disease [AD] (Alcolea et al., 2015; Suarez-Calvet et al., 2016). In pilot studies of 20 older adults at risk of AD, we previously observed notable relationships between cerebro-spinal fluid (CSF) inflammatory markers and AD biomarkers (Breitner et al., 2016). We have now followed up those findings by investigating baseline CSF markers of inflammation and of AD pathology in the full complement of volunteers from the lumbar-puncture (LP) sub-study of the double-blind, placebo-controlled, cognitive and biomarker-endpoint INTREPAD trial of low-dose naproxen. INTREPAD randomized 217 healthy older individuals with a parental or multiple-sibling family history of AD. LP volunteers numbered 106. In their CSF we assayed the typical AD biomarkers (amyloid-beta1–42 [Aß1–42] and total-tau [t-tau]), as well as 45 markers of inflammation using a combination of the Mesoscale (MSD) (Mesoscale Discovery, Rockville, MD) and the Milliplex (EMD-Millipore, Billerica, MA) platforms. The two methods measured 21 markers in common. After imposing several quality-control (QC) measures, we compared the techniques’ agreement and range of values for each analyte. When agreement was good, we chose the method that provided more QC-acceptable readings, or the technique that better avoided apparent ceiling or floor effects. We excluded analytes with poor agreement if neither offered at least 50 QC-acceptable readings. We then used multiple linear regression models to investigate the relationships between CSF inflammatory marker levels and the AD biomarkers t-tau, Aß1–42, or the t-tau/Aß1–42 ratio. All models adjusted for age, gender and APOE e4 status. Milliplex and MSD measurements were broadly consistent. Twenty-seven markers had usable measurements (> 50 QC-acceptable readings) from at least one platform (Table 1). Among these we found statistically significant associations between 14 pro-inflammatory markers and increase in Aß1–42, t-tau or the t-tau/Aß1–42 ratio. Using baseline CSF samples from INTREPAD, we confirmed and expanded upon pilot findings of strong relationships between CSF inflammatory markers and bio-indicators of AD pathogenesis. These results suggest the possibility of important AD biomarker effects of naproxen treatment in INTREPAD, results from which will be available later this year. Fourteen of 27 QC-acceptable markers were significantly associated (*p<0.05, **p<0.01, ***p<0.005) with (black) normalized (log transformed) t-tau/Aβ1–42 ratio, (red) normalized (log transformed) t-tau, or (blue) Aβ1–42. Alterations in tau, which is typically thought to indicate neurodegenerative change, appeared to “drive” most of these results Fourteen of 27 QC-acceptable markers were significantly associated (*p<0.05, **p<0.01, ***p<0.005) with (black) normalized (log transformed) t-tau/Aβ1–42 ratio, (red) normalized (log transformed) t-tau, or (blue) Aβ1–42. Alterations in tau, which is typically thought to indicate neurodegenerative change, appeared to “drive” most of these results
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".